GPS is classified as a GNSS (Global Navigation Satellite System) that has reached fully operational capability in 1995, and is developed by the United States Department of Defense. GPS is widely used today as a system that allows navigation in a myriad of domains, from space, aeronautics to maritime. It is also widely used in other applications such as map-making, land-surveying, time reference keeping and serves different communities such as the military, commercial and scientific.
Galileo is a European GNSS planed to be operational in 2012. It is being developed by the European Union and the European Space Agency. Galileo will introduce new signals with distinct characteristics of GPS and will provide a higher precision than is currently available with GPS. New signals will include a pilot tone signal, which has no navigation data modulation.
GPS and Galileo operate using the same principle: the receiver determines its position using distance measurements between itself and visible satellites. This is achieved by measuring the time elapsed between satellite transmission and receiver reception, and also by demodulating the received signal that contains the satellite position data, also known as ephemeris. Once the measurements are obtained and the navigation message demodulated, the user position is easily determined by solving a set of non-linear equations, where the number of unknowns are the three coordinates. Since the receiver does not have a perfectly accurate clock, besides three satellites for determination of three coordinates, an additional satellite measurement in needed. Furthermore, since the signals transmitted by the satellites are affected by propagation delays, such as due to ionosphere, additional algorithms are required by the receiver to correct the performed measurements.
GPS and Galileo signals are considerably weak when they arrive at the receiver. Furthermore such signals can be easily obstructed, for example due to a tall building, or can be attenuated due to, for example, the canopy of trees. This results in the inability to determine a valid navigation solution. Furthermore, when the dynamics between the satellite and user are very high and if no external aiding is used, an additional error may distort the navigation solution, usually termed dynamic stress error.
INS consists of an IMU (Inertial Measurement Unit) that is combined with a set of algorithms that provide the position, velocity and attitude of a platform by measuring the linear and angular accelerations applied to the system in an inertial reference frame. INS is widely used in navigation systems such as in aircraft, as it is immune to interference and offers a reliable an independent means for navigation. INS requires periodic calibration and maintenance at a period that typically depends on the quality and cost of the sensors. In some cases, using low cost sensors, the calibration is required every second to avoid excessive drifting.
To overcome individual INS and GNSS problems as those mentioned before, a widely used technique consists in integrating INS with GNSS, where each of the systems complement each other. In a prior art system, an additional technique consists in increasing the integration times of GNSS signals so that, during the integration, the navigation solution is provided by the INS. Increasing the integration time of GNSS signals is a usual technique employed in GNSS signal tracking to allow detection of weaker signals, but results in decreased sensibility due to dynamics unless external aid is available from, for example, the INS. Another limitation of long integrations is that its duration is limited to the navigation data period of GNSS signals. With Galileo pilot tone signal, since no navigation data is modulated, this will not be a problem but attention is still required not to loose required sensibility due to dynamics.
Different techniques can be used to integrate GNSS and INS, using different levels of integration, ranging from uncoupled, loosely coupled, tightly coupled to ultra-tightly coupled. Recent attempts to use ultra-tight integration between GNSS and INS techniques rely on replacing the traditional tracking structures with a KF (Kalman Filter). This technique allows elimination of bandwidth limitations imposed by filters within the DLLs (Delayed Locked Loops) and PLLs (Phase Locked Loops). Furthermore it allows multi-satellite tracking, which permits more robust satellite tracking as one signal aids the other since the navigation and the tracking are now performed together. In the ultra-tight approach, the combined GNSS-INS system provides the necessary feedback to aid the code and carrier phase tracking. Tracking of these components consists in aligning the incoming signal's code and carrier phase with the local generated replica in a permanent feedback and correction mechanism, requiring the use of code and carrier phase discriminators that provide an estimate of the error.
The bandwidth limitation of the DLL and PLL can affect the quality of the navigation solution, principally if the receiver clock or the inertial aiding quality are not good, resulting in an additional error in real and imaginary components of a correlator output COUT, also termed the I and Q components. One prior art technique is to model clock and the just mentioned I and Q errors in the KF in a tight coupling or, using an ultra-tightly coupled architecture as exemplified in the patent with international publication number WO 2005/124278 A1. In this type of approach, the I and Q data is used and the filter bandwidth is no longer a system design parameter, but intrinsically determined by the KF at every update epoch of the KF. However, a series on non-linear transformations and assumptions of the I and Q data are required. In prior art systems, as described in the United States patent with publication number US 2006/0161329 A1 and publication number U.S. Pat. No. 7,151,486 B2, the I and Q data are modelled as functions of simple cosine and sine with given amplitudes and white Gaussian noise, and transformations of measured I and Q data using discriminators, that in turn are related with KF states assuming the above mentioned simplified model. This model and transformations result in approximations that deteriorate the navigation solution, therefore making more difficult to track the GNSS in harsh environments, such as when the signal strength is low; when the dynamics are high; when the quality of the aiding or the clock is degraded. In both U.S. Pat. No. 7,151,486 B2 and US 2006/0161329 A1 the tracking modules provide residuals resulting from the transformations to navigation filter modules and therefore the integration between the I and Q data and the inertial sensor is not performed in the same filter.
An additional limitation in prior art systems is the tracking of low strength GPS signals often resulting in false signal lock, degrading the navigation solution. This problem is typical in tight coupling, since very small PLL and DLL bandwidths and multi-satellite tracking allow operation in noisier scenarios. The same problem applies in ultra-tight coupling. Therefore, in both tight and ultra-tight coupling, special attention is required in order to provide optimal signal lock detection.
In other prior art systems, the GNSS antenna and the inertial sensor and receiver are physical separated from each other and from the receiver, and therefore when installed, such as in an aircraft, due to the vibrations and other small movements in the structure, additional processing effort is required to remove, smooth or estimate such variations, that can affect the quality of the tracking in the tight ultra-tight coupling.